Jingjing  Wu

Jingjing Wu

Contact information

Phone number

Office: +1 (403) 220-6303

Location

Office: MS548

I'm looking for...

Research partners

I am recruiting both MSc and Ph.D graduates. Those who have strong mathematical/statistical background (a must for PhD applicants) and high computing capability are especially encouraged to apply. 

Background

Educational Background

PhD Statistics, University of Alberta, 2008

MSc Probability, Beijing Normal University, 2002

BSc Computational Mathematics and Applied Software, Minzu University of China, 1999

Research

Areas of Research

Statistics and Biostatistics
  • Minimum distance estimation
  • Non/semi-parametric models
  • Mixture models
  • Regression models
  • Efficiency and robustness
  • Survival analysis
  • Feature selection
  • Classification
  • Statistical genetics

Courses

Course number Course title Semester
STAT 601.21 Topics in Probability and Statistics (Adv. Stat. Methods & App) Fall
STAT 701 Theory of Probability I Winter

Awards

  • Excellence in Supervision Nominee, Graduate Students' Association, University of Calgary. 2017
  • GREAT Supervisor Award, Faculty of Graduate Studies, University of Calgary. 2017
  • Pierre-Robillard Award, Statistical Society of Canada. 2008
  • J.M. Mitchell Graduate Research Prize, University of Alberta. 2006

Publications

  • ***Note: My graduate or postdoc co-authors are annotated by †. Publications before year 2020 can be found on Scopus and Google Scholar.
  • QDA classification of high-dimensional data with rare and weak signals. Hanning Chen†, Qiang Zhao and Jingjing Wu. Advances in Data Analysis and Classification, to appear. (2023)
  • Minimum profile Hellinger distance estimation of semiparametric multiple linear regression models. Jiang Li† and Jingjing Wu. Journal of Statistical Computation and Simulation, to appear. (2023)
  • Robust variable selection with exponential squared loss for partially linear spatial autoregressive models. Xiuli Wang, Jingchang Shao, Jingjing Wu and Qiang Zhao. Annals of the Institute of Statistical Mathematics, to appear. (2023)
  • Semiparametric modelling of two-component mixtures with stochastic dominance. Jingjing Wu, Tasnima Abedin† and Qiang Zhao. Annals of the Institute of Statistical Mathematics, 75(1). 39-70. (2023)
  • Bi-level variable selection in semiparametric transformation mixture cure models for right-censored data. Jingjing Wu, Xuewen Lu and Wenyan Zhong†. Communications in Statistics – Simulation and Computation, 52(7). 3006-3025. (2023)
  • Interaction-integrated linear mixed model reveals 3D-genetic basis underlying Autism. Qing Li, Chen Cao, Deshan Perera, Jingni He, Jiayi Bian†, Xingyu Chen, Feeha Azeem, Aaron Howe, Billie Au, Jingjing Wu, Jun Yan and Quan Long. Genomics, 115(2). 1-13. (2023)
  • Non-parametric comparison and classification of two large-scale populations. Seyed Kamran Ghoreishi, Jingjing Wu and Ghazal S. Ghoreishi. Journal of Korean Statistical Society, 52(1). 234-247. (2023)
  • Robust and efficient estimation for nonlinear model based on composite quantile regression with missing covariates. Qiang Zhao, Chao Zhang, Jingjing Wu and Xiuli Wang. AIMS Mathematics, 7(5). 8127-8146. (2022)
  • Robust and efficient estimation of GARCH models based on Hellinger distance. Qiang Zhao, Liang Chen† and Jingjing Wu. Journal of Applied Statistics, 49(15). 3976-4002. (2022)
  • A two-component nonparametric mixture model with stochastic dominance. Jingjing Wu and Tasnima Abedin†. Journal of the Korean Statistical Society, 50(4). 1029-1057. (2021)
  • Minimum profile Hellinger distance estimation for semiparametric simple linear regression model. Jiang Li† and Jingjing Wu. Springer Proceedings in Mathematics and Statistics, 375. 1-30. (2021)
  • Semiparametric regression with the U-shaped baseline hazard function in the additive hazards model under general censoring mechanisms. Shabnam Fani†, Hua Shen, Xuewen Lu and Jingjing Wu. Journal of Statistical Computation and Simulation, 91(16). 3255-3282. (2021)
  • Bi-level variable selection in semiparametric transformation models with right-censored data. Wenyan Zhong†, Xuewen Lu and Jingjing Wu. Computational Statistics, 36(3). 1661-1692. (2021)
  • Bayesian analysis of restricted penalized empirical likelihood. Mahdieh Bayati, Seyed K. Ghoreishi and Jingjing Wu. Computational Statistics, 36(2). 1321-1339. (2021)
  • Empirical estimates for heteroscedastic hierarchical dynamic normal models. Seyed K. Ghoreishi and Jingjing Wu. Journal of the Korean Statistical Society, 50(2). 528-543. (2021)
  • kTWAS: integrating kernel-machine with transcriptome-wide association studies improves statistical power and reveals novel genes. Chen Cao, Devin Kwok, Shannon Edie, Qing Li, Bowei Ding†, Pathum Kossinna, Simone Campbell, Jingjing Wu, Matthew Greenberg, Quan Long. Briefings in Bioinformatics, 22(4). 1-16. (2021)
  • Power analysis of transcriptome-wide association study: implications for practical protocol choice. Chen Cao, Bowei Ding†, Qing Li, Devin Kwok, Jingjing Wu and Quan Long. PLOS Genetics, 17(2). 1-20. (2021)
  • Restricted empirical likelihood estimation for time series autoregressive models. Mahdieh Bayati, Seyed K. Ghoreishi and Jingjing Wu. Journal of Statistical Theory and Applications, 20(1). 11-20. (2021)
  • Adaptive thresholding estimator for differential association structures in two independent contingency tables. Seyed K. Ghoreishi and Jingjing Wu. Hacettepe Journal of Mathematics & Statistics, 49(4). 1480-1492. (2020)
  • An empirical classification procedure for nonparametric mixture models. Qiang Zhao, Rohana J. Karunamuni and Jingjing Wu. Journal of the Korean Statistical Society, 49(3). 924-952. (2020)
  • Prevalence, risk factors and genotype distribution of Toxoplasma gondii DNA in soil in China. Wei Cong, Nianzhang Zhang, Ruisi Hu, Fengcai Zou, Yang Zou, Wenyan Zhong†, Jingjing Wu, Christopher J. Fallaize, Xingquan Zhu and Hany M. Elsheikha. Ecotoxicology and Environmental Safety, 189. 1-7. (2020)